Building agents for power trading agent competition (TAC)

Sustainable power system requires not only environmentally friendly, cost-efficient and renewable energy, but more efficient than the allocation. Power Trading Agent Competition (Power TAC) is organized by the independent transaction AAMAS annual contest, which models the future energy market. Part...

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Main Author: Chen, Jiaqi
Other Authors: Bo An
Format: Final Year Project
Language:English
Published: 2016
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Online Access:http://hdl.handle.net/10356/67397
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-673972023-03-03T20:31:22Z Building agents for power trading agent competition (TAC) Chen, Jiaqi Bo An School of Computer Engineering DRNTU::Science Sustainable power system requires not only environmentally friendly, cost-efficient and renewable energy, but more efficient than the allocation. Power Trading Agent Competition (Power TAC) is organized by the independent transaction AAMAS annual contest, which models the future energy market. Parties involved in simulation model including customers, power producers, and brokers. Customer representatives of both power consumption models, such as daily necessities, small to large -scale enterprises, multi- residential buildings, wind farms, solar panels and electric vehicle owners. At the same time who can resell excess electricity market parties. Brokers aim to provide electricity in the wholesale market for the energy customers and trading buy low sell high, and carefully balance their portfolio of power supply and demand profit. Power tariff duties may be generally who consume power or power purchase price from customers who generate electricity, and additional resale customers. In the wholesale market, the broker can buy or sell by the producers, industrial sites and other power brokers. In summary, profit maximizer broker acts as an intermediary in the competition. The goal of the project is to establish a trade agency, to maximize profits provided scenarios. Therefore, we studied a number of other universities and research work already completed brokers. In addition, we also investigated a number of classical algorithms in order to make some assumptions, and through the establishment of a proxy simple scenario. Bachelor of Engineering (Computer Science) 2016-05-16T06:57:50Z 2016-05-16T06:57:50Z 2016 Final Year Project (FYP) http://hdl.handle.net/10356/67397 en Nanyang Technological University 39 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Science
spellingShingle DRNTU::Science
Chen, Jiaqi
Building agents for power trading agent competition (TAC)
description Sustainable power system requires not only environmentally friendly, cost-efficient and renewable energy, but more efficient than the allocation. Power Trading Agent Competition (Power TAC) is organized by the independent transaction AAMAS annual contest, which models the future energy market. Parties involved in simulation model including customers, power producers, and brokers. Customer representatives of both power consumption models, such as daily necessities, small to large -scale enterprises, multi- residential buildings, wind farms, solar panels and electric vehicle owners. At the same time who can resell excess electricity market parties. Brokers aim to provide electricity in the wholesale market for the energy customers and trading buy low sell high, and carefully balance their portfolio of power supply and demand profit. Power tariff duties may be generally who consume power or power purchase price from customers who generate electricity, and additional resale customers. In the wholesale market, the broker can buy or sell by the producers, industrial sites and other power brokers. In summary, profit maximizer broker acts as an intermediary in the competition. The goal of the project is to establish a trade agency, to maximize profits provided scenarios. Therefore, we studied a number of other universities and research work already completed brokers. In addition, we also investigated a number of classical algorithms in order to make some assumptions, and through the establishment of a proxy simple scenario.
author2 Bo An
author_facet Bo An
Chen, Jiaqi
format Final Year Project
author Chen, Jiaqi
author_sort Chen, Jiaqi
title Building agents for power trading agent competition (TAC)
title_short Building agents for power trading agent competition (TAC)
title_full Building agents for power trading agent competition (TAC)
title_fullStr Building agents for power trading agent competition (TAC)
title_full_unstemmed Building agents for power trading agent competition (TAC)
title_sort building agents for power trading agent competition (tac)
publishDate 2016
url http://hdl.handle.net/10356/67397
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